Publications

Image-Guided Brachytherapy for Rectal Cancer: Reviewing the Past Two Decades of Clinical Investigation
T. Vuong
Aurelie Garant
Veronique Vendrely
Remi Nout
André-Guy Martin
Shirin A. Enger
Ervin Podgorsak
Belal Moftah
S. Devic
2022-10-01
Cancers (publié)
doi.org
Lifelong Topological Visual Navigation
Rey Reza Wiyatno
Anqi Xu
Liam Paull
Commonly, learning-based topological navigation approaches produce a local policy while preserving some loose connectivity of the space thro… (voir plus)ugh a topological map. Nevertheless, spurious or missing edges in the topological graph often lead to navigation failure. In this work, we propose a sampling-based graph building method, which results in sparser graphs yet with higher navigation performance compared to baseline methods. We also propose graph maintenance strategies that eliminate spurious edges and expand the graph as needed, which improves lifelong navigation performance. Unlike controllers that learn from fixed training environments, we show that our model can be fine-tuned using only a small number of collected trajectory images from a real-world environment where the agent is deployed. We demonstrate successful navigation after fine-tuning on real-world environments, and notably show significant navigation improvements over time by applying our lifelong graph maintenance strategies.
2022-10-01
IEEE Robotics and Automation Letters (publié)
doi.org
arxiv.org
MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record
Yuri Ahuja
Yuesong Zou
Aman Verma
David Buckeridge
Yue Li
2022-10-01
Journal of Biomedical Informatics (publié)
doi.org
Predicting histopathology markers of endometrial carcinoma with a quantitative image analysis approach based on spherical harmonics in multiparametric MRI.
Thierry L. Lefebvre
Ozan Ciga
Sahir Rai Bhatnagar
Yoshiko Ueno
S. Saif
Eric Winter-Reinhold
Anthony Dohan
P. Soyer
Reza Forghani
Kaleem Siddiqi
Jan Seuntjens
Caroline Reinhold
Peter Savadjiev
2022-10-01
Diagnostic and Interventional Imaging (publié)
doi.org
Synthetic data as an enabler for machine learning applications in medicine
Jean-Francois Rajotte
Robert Bergen
David Buckeridge
Khaled El Emam
Raymond Ng
Elissa Strome
2022-10-01
iScience (publié)
doi.org
The use of artificial intelligence and virtual reality in doctor-patient risk communication: A scoping review.
Ryan Antel
Samira Abbasgholizadeh-Rahimi
Elena Guadagno
Jason M. Harley
Dan Poenaru
2022-10-01
Patient Education and Counseling (publié)
doi.org
Evolution of cell size control is canalized towards adders or sizers by cell cycle structure and selective pressures
Felix Proulx-Giraldeau
Jan M Skotheim
Paul François
Cell size is controlled to be within a specific range to support physiological function. To control their size, cells use diverse mechanisms… (voir plus) ranging from ‘sizers’, in which differences in cell size are compensated for in a single cell division cycle, to ‘adders’, in which a constant amount of cell growth occurs in each cell cycle. This diversity raises the question why a particular cell would implement one rather than another mechanism? To address this question, we performed a series of simulations evolving cell size control networks. The size control mechanism that evolved was influenced by both cell cycle structure and specific selection pressures. Moreover, evolved networks recapitulated known size control properties of naturally occurring networks. If the mechanism is based on a G1 size control and an S/G2/M timer, as found for budding yeast and some human cells, adders likely evolve. But, if the G1 phase is significantly longer than the S/G2/M phase, as is often the case in mammalian cells in vivo, sizers become more likely. Sizers also evolve when the cell cycle structure is inverted so that G1 is a timer, while S/G2/M performs size control, as is the case for the fission yeast S. pombe. For some size control networks, cell size consistently decreases in each cycle until a burst of cell cycle inhibitor drives an extended G1 phase much like the cell division cycle of the green algae Chlamydomonas. That these size control networks evolved such self-organized criticality shows how the evolution of complex systems can drive the emergence of critical processes.
2022-09-30
eLife (publié)
doi.org
SPeCiaL: Self-Supervised Pretraining for Continual Learning
Lucas Caccia
Joelle Pineau
2022-09-28
Continual Semi-Supervised Learning (publié)
doi.org
arxiv.org
From analytic to synthetic-organizational pluralisms: A pluralistic enactive psychiatry
Christophe Gauld
Kristopher Nielsen
Manon Job
Hugo Bottemanne
Guillaume Dumas
2022-09-27
Frontiers in Psychiatry (publié)
doi.org
Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning
Jean-Pierre R. Falet
Joshua D. Durso-Finley
Brennan Nichyporuk
Julien Schroeter
Francesca Bovis
Maria-Pia Sormani
Doina Precup
Tal Arbel
Douglas Arnold
2022-09-26
Nature Communications (publié)
doi.org
FedShuffle: Recipes for Better Use of Local Work in Federated Learning
Samuel Horváth
Maziar Sanjabi
Lin Xiao
Peter Richtárik
Michael Rabbat
The practice of applying several local updates before aggregation across clients has been empirically shown to be a successful approach to o… (voir plus)vercoming the communication bottleneck in Federated Learning (FL). Such methods are usually implemented by having clients perform one or more epochs of local training per round while randomly reshuffling their finite dataset in each epoch. Data imbalance, where clients have different numbers of local training samples, is ubiquitous in FL applications, resulting in different clients performing different numbers of local updates in each round. In this work, we propose a general recipe, FedShuffle, that better utilizes the local updates in FL, especially in this regime encompassing random reshuffling and heterogeneity. FedShuffle is the first local update method with theoretical convergence guarantees that incorporates random reshuffling, data imbalance, and client sampling — features that are essential in large-scale cross-device FL. We present a comprehensive theoretical analysis of FedShuffle and show, both theoretically and empirically, that it does not suffer from the objective function mismatch that is present in FL methods that assume homogeneous updates in heterogeneous FL setups, such as FedAvg (McMahan et al., 2017). In addition, by combining the ingredients above, FedShuffle improves upon FedNova (Wang et al., 2020), which was previously proposed to solve this mismatch. Similar to Mime (Karimireddy et al., 2020), we show that FedShuffle with momentum variance reduction (Cutkosky & Orabona, 2019) improves upon non-local methods under a Hessian similarity assumption.
2022-09-26
TMLR (accepté)
doi.org
openreview.net
The 5-year longitudinal diagnostic profile and health services utilization of patients treated with electroconvulsive therapy in Quebec: a population-based study
Simon Lafrenière
Fatemeh Gholi-Zadeh-Kharrat
Caroline Sirois
Victoria Massamba
Louis Rochette
Camille Brousseau-Paradis
Simon Patry
Christian Gagné
Morgane Lemasson
Geneviève Gariépy
Chantal Mérette
Elham Rahme
Alain Lesage
2022-09-26
Social Psychiatry and Psychiatric Epidemiology (publié)
doi.org